The HASTE project, a SSF-funded project on computational science and big data, takes a holistic approach to new, intelligent ways of processing and managing very large amounts of microscopy images to leverage the imminent explosion of image data from modern experimental setups in the biosciences. One central idea is to represent datasets as intelligently formed and maintained information hierarchies, and to prioritize data acquisition and analysis to certain regions/sections of data based on automatically obtained metrics for usefulness and interestingness. The project is a collaboration between the Wählby lab (PI),  Hellander lab (co-PI), both at the Department of Information Technology, Uppsala University, the Spjuth lab (co-PI) at ...
Read More
In multicellular systems, cells of different types interact in various ways, both mechanically and chemically, to regulate complex processes. There is a large computational gap between detailed models of sub-cellular, molecular processes in single cells, and models of multicellular systems comprising of large numbers of interacting cells such as bacterial colonies, tissue and tumors. In the lab we seek to bridge this gap. We also develop new simulation methodology for modeling specific biological systems together with collaborators. Studying the scaling mechanisms of cartilage sheets During embryo development cartilaginous structures assemble that later densify into bone and form the basis for ...
Read More
The integration between on the one hand data, modeling and algorithms, and on the other hand the specification, coordination and execution of large scale and data-intensive computational experiments poses a fundamental problem in all scientific disciplines relying on modeling and simulation. Today it is largely left to the modeler or engineer to manually tune models to fit data, to choose algorithms, to configure simulation workflows and to analyze simulation result. This is a big burden to place on e.g. a biologist who is mainly interested in how she can use modeling and simulation to learn new things about a biological ...
Read More
Open source computational science and engineering (CSE) software is an integral part of methodology-oriented computational research and a priority in the group. Due to the ongoing transformation of e-infrastructure to clouds, methods and workflows that promote horizontal scalability and elasticity for cloud applications are needed, and this may in many cases require re-thinking of how we best make use of computational resources. Other important questions include reproducibility and handling of large and complex data.  Selected recent publications:  B. Drawert, A. Hellander, B. Bales, D. Banerjee, G. Bellesia, B.J. Daigle, Jr. G. Douglas, M. Gu, A. Gupta, S. Hellander, C. Horuk, D. Nath, ...
Read More
Life spans in size from small organisms consisting of single cells to complex organisms built up of billions of cells. Even the single-cell organisms are challenging to fully understand and study—their function is dependent on a rich set of reaction networks. Important molecules inside a cell may exist in only a few copies, and that makes them exceedingly difficult and costly to study. The aim of our research is to develop algorithms and software that can assist in discoveries in basic science and medicine. We use mathematical models to describe how molecules move and interact inside cells, and then simulate ...
Read More